Pass or Fail? Prediction of Students’ Exam Outcomes from Self-reported Measures and Study Activities

Bianca Clavio Christensen, Brian Bemman, Hendrik Knoche, Rikke Gade

Research output: Contribution to journalJournal articleResearchpeer-review

3 Citations (Scopus)
151 Downloads (Pure)

Abstract

Technical educations often exhibit poor student performance and consequently high rates of attrition. Providing students with early feedback on their learning progress can assist them in self-study activities or in their decision-making process regarding a change in educational direction. In this paper, we present a set of instruments designed to identify at-risk undergraduate students in a Problem-based Learning (PBL) university, using an introductory programming course as a case study. Collectively, these instruments form the basis of a proposed learning ecosystem designed to identify struggling students by predicting their final exam grades in this course. We implemented this ecosystem and analyzed how well the obtained data predicted the final exam scores. Best-subset-regression and lasso regressions yielded several significant predictors. Apart from relevant predictors known from the literature on exam scores and drop-out factors such as midterm exam results and student retention factors, data from self-assessment quizzes, peer reviewing activities, and interactive online exercises helped predict exam performance and identified struggling students.
Original languageEnglish
JournalInteraction Design and Architecture(s)
Volume39
Pages (from-to)44-60
Number of pages17
ISSN1826-9745
Publication statusPublished - 2019

Bibliographical note

Special issue on 'Smart Learning Ecosystems - technologies, places, and human-centered design'

Keywords

  • Academic performance
  • Student retention
  • Learning Management System
  • Learning Tools Interoperability
  • Problem-Based Learning
  • Flipped learning

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  • Stars, Crests and Medals: Visual Badge Design Framework to Gamify and Certify Online Learning

    Hougaard, B. I. & Knoche, H., 28 Jul 2020, Interactivity, Game Creation, Design, Learning, and Innovation: 8th EAI International Conference, ArtsIT 2019, and 4th EAI International Conference, DLI 2019, Aalborg, Denmark, November 6–8, 2019, Proceedings. Brooks, A. & Brooks, E. I. (eds.). Cham: Springer, p. 406-414 9 p. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 328).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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    2 Citations (Scopus)
    89 Downloads (Pure)
  • Identifying Students Struggling in Courses by Analyzing Exam Grades, Self-reported Measures and Study Activities

    Christensen, B. C., Bemman, B., Knoche, H. & Gade, R., 2018, The Interplay of Data, Technology, Place and People for Smart Learning: Proceedings of the 3rd International Conference on Smart Learning Ecosystems and Regional Development. Knoche, H., Popescu, E. & Cartelli, A. (eds.). Springer, p. 167-176 10 p. (Smart Innovation, Systems and Technologies, Vol. 95).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access
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    213 Downloads (Pure)

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